base correlations

plots.py

@@ -1048,6 +1048,59 @@ class QualtricsPlotsMixin:
         chart = self._save_plot(chart, title)
         return chart
 
+    def plot_speaking_style_color_correlation(
+        self,
+        data: pl.LazyFrame | pl.DataFrame | None = None,
+        title: str = "Speaking Style and Voice Scale 1-10 Correlations<br>(Average by Color)",
+        width: int | str | None = None,
+        height: int | None = None,
+    ) -> alt.Chart:
+        """Plot high-level correlation showing one bar per speaking style color.
+        
+        Original use-case: "I want to create high-level correlation plots between
+        'green, blue, orange, red' speaking styles and the 'voice scale scores'.
+        I want to go to one plot with one bar for each color."
+        
+        Args:
+            data: DataFrame with columns [Color, correlation, n_traits] from 
+                  utils.transform_speaking_style_color_correlation
+            title: Chart title (supports <br> for line breaks)
+            width: Chart width in pixels
+            height: Chart height in pixels
+        
+        Returns:
+            Altair chart with one bar per speaking style color
+        """
+        df = self._ensure_dataframe(data)
+        
+        # Conditional color based on sign (matches plot_speaking_style_correlation)
+        chart = alt.Chart(df.to_pandas()).mark_bar().encode(
+            x=alt.X('Color:N', 
+                    title=None, 
+                    axis=alt.Axis(labelAngle=0),
+                    sort=["Green", "Blue", "Orange", "Red"]),
+            y=alt.Y('correlation:Q', 
+                    title='Average Correlation',
+                    scale=alt.Scale(domain=[-1, 1])),
+            color=alt.condition(
+                alt.datum.correlation >= 0,
+                alt.value('green'),
+                alt.value('red')
+            ),
+            tooltip=[
+                alt.Tooltip('Color:N', title='Speaking Style'),
+                alt.Tooltip('correlation:Q', format='.3f', title='Avg Correlation'),
+                alt.Tooltip('n_traits:Q', title='# Traits')
+            ]
+        ).properties(
+            title=self._process_title(title),
+            width=width or 400,
+            height=height or 350
+        )
+        
+        chart = self._save_plot(chart, title)
+        return chart
+
     def plot_demographic_distribution(
         self,
         column: str,